Diffusion MRI studies in vascular cognitive impairment and dementia

Discriminating VCID subgroups: A diffusion MRI multi-model fusion approach

BACKGROUND

Vascular cognitive impairment and dementia (VCID) and Alzheimer's disease are predominant diseases among the aging population resulting in decline of various cognitive domains. Diffusion weighted MRI (DW-MRI) has been shown to be a promising aid in the diagnosis of such diseases. However, there are various models of DW-MRI and the interpretation of diffusion metrics depends on the model used in fitting data. Most previous studies are entirely based on parameters calculated from a single diffusion model.

NEW METHOD

We employ a data fusion framework wherein diffusion metrics from different models such as diffusion tensor imaging, diffusion kurtosis imaging and constrained spherical deconvolution model are fused using well known blind source separation approach to investigate white matter microstructural changes in population comprising of controls and VCID subgroups. Multiple comparisons between subject groups and prediction analysis using features from individual models and proposed fusion model are carried out to evaluate performance of proposed method.

RESULTS

Diffusion features from individual models successfully distinguished between controls and disease groups, but failed to differentiate between disease groups, whereas fusion approach showed group differences between disease groups too. WM tracts showing significant differences are superior longitudinal fasciculus, anterior thalamic radiation, arcuate fasciculus, optic radiation and corticospinal tract.

COMPARISON WITH EXISTING METHOD

ROC analysis showed increased AUC for fusion (AUC = 0.913, averaged across groups and tracts) compared to that of uni-model features (AUC = 0.77) demonstrating increased sensitivity of proposed method.

CONCLUSION

Overall our results highlight the benefits of multi-model fusion approach, providing improved sensitivity in discriminating VCID subgroups.

Diffusion tensor imaging investigations in Alzheimer's disease: the resurgence of white matter compromise in the cortical dysfunction of the aging brain

Diffusion tensor imaging (DTI) is a sophisticated MRI-based neuroimaging technique that enables in vivo quantification of differences in molecular diffusion at the cellular level. Owing to the highly directional architecture of white matter (WM), DTI is providing important clues of the structure and geometric organization of this neural compartment. Since DTI can detect changes even in the case of radiologically "normal" appearing WM, researchers are using the technique for the study of WM integrity at the initial stages of the most common neurodegenerative disorders. Along with a well characterized cortical pathology (neuritic plaques and intracellular neurofibrillary tangles), WM changes have been also demonstrated in Alzheimer's disease (AD). However, these changes had been for years found nonliable in the onset and progress of AD, basically due to lack of incriminatory evidence. The use of novel tools such as DTI has enabled the anatomical distribution of WM microstructural damage in the prodromal stages of AD to be gauged and determined, granting a long-delayed protagonic role to WM in the natural history of this highly prevalent neurodegenerative condition.